• Journal of Korean Society of Water and Wastewater
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• v.30 no.6
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• pp.653-662
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• 2016

Recently, advanced metering infrastructure (AMI) has been recognized as a core technology of smart water grid, and the relevant market is growing constantly. In this study, we developed all-in-one smart water meter of the AMI system, which was installed on the test-bed to verify both effectiveness and field applicability in office building water usage. Developed 15 mm-diameter smart water meter is a magneto-resistive digital meter, and measures flow rate and water quality parameters (temperature, conductivity) simultaneously. As a result of the water usage analysis by installing six smart water meters on various purposes in office building water usage, the water usage in shower room showed the highest values as the 1,870 L/day and 26.6 liter per capita day (LPCD). But, the water usage in laboratory was irregular, depending on the many variables. From the analysis of the water usage based on day of the week, the water usage on Monday showed the highest value, and tended to decrease toward the weekend. According to the PCA results and multivariate statistical approaches, the shower room (Group 3) and 2 floor man's restroom sink (Group 1-3) have been classified as a separate group, and the others did not show a significant difference in both water use and water quality aspects. From the analysis of water usage measured in this study, the leak or water quality accident did not occur. Consequently, all-in-one smart water meter developed in this study can measure flow rate and water quality parameters (temperature, conductivity) simultaneously with effective field applicability in office building water usage.

• Korean Journal of Soil Science and Fertilizer
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• v.38 no.4
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• pp.202-210
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• 2005

Since understanding on spatial variability of a field is essential to pursue precision agricultural technology, a field study for field variability and variable rate fertilization of nitrogen in a direct seeding paddy was attempted. Variable rate application of nitrogen was designed with soil test, and field application was tested in a direct seeding paddy in the Kimje, Jeonbuk, Korea. The grid samples of soil was collected from the field of which unit size was 35 m by 112 m on February before irrigating of the field. Soil organic matter, available phosphate and silicate, and extractable potassium were analyzed. Variable rate fertilizer recommendation maps of nitrogen for high yielding, HY, and low input sustainable agriculture, LISA, were derived based on the soil analysis. Direct seeding of rice was performed for variable rate treatment, VRT, for the experimental plot in 2001 and 2002, and so did for three volunteer farmers' field in 2003. Yield mapping was performed by harvesting. Economic feasibility of direct seeding of rice by variable rate fertilization was evaluated. Though increased yield of variable rate application and benefit of reducing fertilizer use and environmental impact, the cost for soil test exceeded the total reduced fertilizer cost.

• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.76-90
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• 2006

Sensor network consists of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it. The life time of each node in the sensor network significantly affects the life time of whole sensor network. A node which drained out its battery may incur the partition of whole network in some network topology The life time of each node depends on the battery capacity of each node. Therefore if all sensor nodes in the network live evenly long, the life time of the network will be longer. In this paper, we propose Cluster-Based Power-Efficient Routing (CBPER) Protocol which provides scalable and efficient data delivery to multiple mobile sinks. Previous r(luting protocols, such as Directed Diffusion and TTDD, need to flood many control packets to support multiple mobile sinks and many sources, causing nodes to consume their battery. In CBPER, we use the fact that sensor nodes are stationary and location-aware to construct and maintain the permanent grid structure, which makes nodes live longer by reducing the number of the flooding control packets. We have evaluated CBPER performance with TTDD. Our results show that CBPER is more power-efficient routing protocol than TTDD.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.28-38
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• 2004

The purpose of this study is to analyze the urban hydrologic state by the use of GIS, resolution and interpolation. The determination coefficient($R^2$) and Regression Formula were derived from the contour of digital map for the accuracy, and DEM data was made by using TIN interpolation by the size of the grid. By using the observed DEM data, topographical factors were extracted from the small basin, size, the width of a basin and the slope, and were applied in the urban runoff model. Through the model, we tried to find out the most suitable runoff model in a small basin of Yosu-Munsu area. As a result of applying models to the drainage considered, the runoff hydrograph estimated by SWMM model was closer to the observed one than that estimated by ILLUDAS model. The difference between the runoff hydrograph by SWMM and the observed one is maximum error of 19%, minimum error of 5% and average error of 13%. The influence of duration in contrast to pick time is insignificant in a urban small basin. As a conclusion of this study, SWMM model was more suitable and applicable for the urban runoff model than ILLUDAS model due to its accuracy and various abilities.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.9
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• pp.217-224
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• 2019

Recently, sensor networks are built and used on many kinds of fields such as home, traffic, medical treatment and power grid. Sensing data manipulation on these fields could be a serious threat on property and safety. Thus, a proper way to block sensing data manipulation is necessary. In this paper, we propose IoT(Internet of Things) sensing data validation mechanism based on data obfuscation and variance analysis to remove manipulated sensing data effectively. IoT sensor device modulates sensing data with obfuscation function and sends it to a user. The user demodulates received data to use it. Fake data which are not modulated with proper obfuscation function show different variance aspect with valid data. Our proposed mechanism thus can detect fake data by analyzing data variance. Finally, we measured data validation time for performance analysis. As a result, block rate for false data was improved by up to 1.45 times compared with the existing technique and false alarm rate was 0.1~2.0%. In addition, the validation time on the low-power, low-performance IoT sensor device was measured. Compared to the RSA encryption method, which increased to 2.5969 seconds according to the increase of the data amount, the proposed method showed high validation efficiency as 0.0003 seconds.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.74-82
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• 2019

The revolution of industry 4.0 is enabling us to build an intelligent connection society called smart cities. The use of renewable energy in particular solar energy is extremely important for modern society due to the growing power demand in smart cities, but its difficult to monitor and manage in each buildings since need to be deploy low energy sensors and information need to be transfer via wireless sensor network (WSN). The Internet of Things (IoT) / low-power wide-area (LPWA) is an emerging WSN technology, to collect and monitor data about environmental and physical electrical / electronics devices conditions in real time. However, providing power to IoT sensor end devices and other public electrical loads such as street lights, etc is an important challenging role because the sensor are usually battery powered and have a limited life time. In this paper, we proposes an efficient solar energy-based power management scheme for smart city based on IoT technology using LoRa wide-area network (LoRaWAN). This approach facilitates to maintain and prevent errors of solar panel based energy systems. The proposed solution maximizing output the power generated from solar panels system to distribute the power to the load and the grid. In this paper, we proved the efficiency of the proposed system with Simulink based system modeling and real-time emulation.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.857-868
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• 2018

The microphysics and spatio-temporal distribution of atmospheric aerosols are responsible for estimating the optical properties at a given location. Its accurate estimation is essential to plan efficient simulation for radiative transfer. For this sake, synergetic use of reanalysis data with optics database was used as a potential tool to precisely derive the aerosol model on the basis of the major representative particulates exist within a model grid. In detail, mixing of aerosol types weighted by aerosol optical depth (AOD) components has been developed. This synergetic aerosol model (SAM) is spectrally extended up to $40{\mu}m$. For the major aerosol event cases, SAM showed that the mixed aerosol particles were totally different from the typical standard aerosol models provided by the radiative transfer model. The correlation among the derived aerosol optical properties along with ground-based observation data has also been compared. The current results will help to improve the radiative transfer model simulation under the real atmospheric environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.577-584
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• 2021

Electrical energy is an essential component in present societies, which is an important basis for our technological society. In the design of new power infrastructure, it is important to consider the psychological aspects of how our culture considers and aspects its development as an integral component of the community environment. The construction of new high voltage overhead transmission lines has become a controversial issue for public policy of government due to social opposition. The members of community are concerned about how these power lines may have an impact on their lives, basically caused by their effects on health and safety. The landscape and visual impact is one of the most impact that can be easily perceived for local community. The computer 3D simulation of new landscape is illustrated by a real life use corresponding to the selection of the power line route with least observability for local community. This paper used ArcGIS(geographic information system tool) for planning, survey, basic route and detailed route, route for implementation of transmission line corridor. Also, the paper showed the map of natural environment, living environment, safety and altitude using database of power line corridor, and transmission siting model was developed by this study. The suggested landscape of computer simulation with lowest visibility on a power line zone can contribute to reducing oppositions of local community and accelerating the construction of new power lines.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1124-1128
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• 2021

As regulations of emissions from ships become more stringent, electric propulsion systems have been increasingly used to solve this problem in vessels ranging from large merchant ships to small and medium-sized ships. Methods for improving the efficiency of the electric propulsion system include the improvement of power sources; the use of a system linked to environmentally friendly power sources, such as batteries, fuel cells, and solar power; and the development of hardware and control methodology for rectifiers, power conversion devices, and propulsion motors. The method using a phase-shifting transformer with diodes has been widely used for rectification. Power semiconductor devices with grid connection to an environmentally friendly power source using DC distribution, a variable speed power source, and the application of small and medium-sized electric propulsion systems have been developed. Accordingly, the demand for active front-end (AFE) rectifiers is increasing. In this study, a method using a neural network rather than a conventional proportional-integral controller was proposed to control the AFE rectifier. Tested controller data were used to design a neural network controller trained through MATLAB/Simulink. The neural network controller was applied to a rectification system designed using PSIM software. The results indicated the effectiveness of improving the waveform and power factor DC output stage according to the load variation. The proposed system can be applied as a rectification system for small and medium-sized environmentally friendly ships.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.339-346
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• 2022

Recently, the resource depletion and climate change problem caused by the massive usage of fossil fuels for electric power generation has become a critical issue worldwide. According to this issue, interest in renewable energy resources that can replace fossil fuels is increasing. Especially, photovoltaic power has gaining much attention because there is no risk of resource exhaustion compared to other energy resources and there are low restrictions on installation of photovoltaic system. In order to use the power generated by the photovoltaic system efficiently, a more accurate photovoltaic power forecasting model is required. So far, even though many machine learning and deep learning-based photovoltaic power forecasting models have been proposed, they showed limited success in terms of interpretability. Deep learning-based forecasting models have the disadvantage of being difficult to explain how the forecasting results are derived. To solve this problem, many studies are being conducted on explainable artificial intelligence technique. The reliability of the model can be secured if it is possible to interpret how the model derives the results. Also, the model can be improved to increase the forecasting accuracy based on the analysis results. Therefore, in this paper, we propose an explainable photovoltaic power forecasting scheme based on BiLSTM (Bidirectional Long Short-Term Memory) and SHAP (SHapley Additive exPlanations).